Markov switching in disaggregate unemployment rates
Chinhui Juhn2002, Empirical Economics
Sign up for access to the world's latest research
checkGet notified about relevant papers
checkSave papers to use in your research
checkJoin the discussion with peers
checkTrack your impact
Abstract
We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in U.S. unemployment rates. We extract the common dynamics among unemployment rates disaggregated for seven age groups. The framework allows analysis of the contribution of demographic factors to secular changes in unemployment rates. In addition, it allows examination of the separate contribution of changes due to asymmetric business cycle fluctuations. We find strong evidence in favor of the common factor and of the switching between high and low unemployment rate regimes. We also find that demographic adjustments can account for a great deal of the secular change in the unemployment rate, particularly the abrupt increase in the 1970s and 1980s and the subsequent decrease.
Related papers
European unemployment nonlinear dynamics over the business cycles: Markov switching approach
Global Business and Economics Review, 2020
The dynamics of European unemployment showed considerable fluctuations and asymmetric behaviour during business cycles over the past decade. The dynamic pattern of unemployment rate demonstrated the significant differences for different countries during its growth and decline periods. To describe the differences in dynamic properties of unemployment rate in different countries and economic situation, we developed the Markov switching autoregressive models with time-varying probabilities of transition between behaviour regimes. The results revealed that the unemployment rate in EU countries during 2000-2016 behaved asymmetrically over the business cycle. Therefore, we got different processes for describing unemployment dynamics in each phase of the economy.
A Markov switching factor-augmented VAR model for analyzing US business cycles and monetary policy
This paper develops a multivariate regime switching monetary policy model for the US economy. To exploit a large dataset we use a factor-augmented VAR with discrete regime shifts, capturing distinct business cycle phases. The transitions between regimes are modelled as time-varying, depending on a broad set of different indicators that may influence business cycle movements. Employing a dataset which consists of a large set of macroeconomic time series spanning the period from 1971Q4 to 2014Q2, the model is then used to draw a picture of the dynamic relationship between business cycle phases and monetary policy. Our results may be summarized as follows. First, we find that lagged prices, the share of people working in construction and the employment in manufacturing serve as good predictors for business cycle transitions. Second, our findings suggest that impulse response functions are in general more persistent in expansionary phases, while being of a more transient nature in recessions.
Asymmetry in the relationship between unemployment and the business cycle
Empirical Economics, 2014
This study analyses asymmetries in the dynamic relationship between unemployment and the business cycle in the UK and the US. Unemployment rates present clear unconditional asymmetry in both countries. Markov switching regime models with two regimes also display clear asymmetries and show that, in the US, the effect of cyclical contractions on unemployment is much stronger than that of expansions, while in the UK it is observed that male unemployment is much more sensitive to cyclical variations than female unemployment.
Business cycle analysis with multivariate Markov switching models
2004
The aim of the paper is to describe the cyclical phases of the economy using multivariate Markov switching models. The class of Markov switching models can be extended in two main directions in a multivariate framework. In the first approach, the switching dynamics are introduced by way of one common latent factor . In the second approach, developed by Krolzig (1997), a VAR model with parameters depending on one common Markov chain is considered (MS VAR). We will extend the MS VAR approach allowing for the presence of specific Markov chain in each equation of the VAR (Multiple Markov Switching VAR models, MMS VAR). Dynamic factor models with regime switches, MS VAR and MMS VAR models allow for a multi-country or a multi-sector simultaneous analysis in the search of common phases which are represented by the states of the switching latent factor. Moreover, in the MMS VAR approach we explore the introduction of correlated Markov chains which allow us to evaluate the relationships among phases in different economies or sectors and introduce causality relationships, which allow a more parsimonious representations. We apply the MMS model in order to study the relationship between cyclical phases of the industrial production in the U.S. and Euro zone. Moreover, we construct a MMS model in order to explore the cyclical relationship between the Euro zone industrial production and the industrial component of the European Sentiment Index (ESI).
Measuring U.S. Business Cycle Using Markov-Switching Model: A Comparison Between Empirical Likelihood Estimation and Parametric Estimations
2019
Markov-switching (MS) model is one of the most popular nonlinear time series models in the literature. However, as there are many methods for parameter estimation, the results including the plot are not similar and become more difficult for researchers to decide on the interpretation. Therefore, this study is conducted as we want to obtain a more sensitive estimation method for the MS model. This study attempts to improve the way we estimate the MS model by developing a more flexible estimator for it to be called a maximum empirical likelihood estimation (MELE). A key point of this method is that a conventional parametric likelihood is replaced by the empirical likelihood function with relatively minor modifications to existing recursive filters. To evaluate the new method’s performance, we apply the MS model to the U.S. business cycle. The estimated results from the MELE are discussed and compared to those from classical parametric estimations. It is found that the empirical likeli...
A New Approach to the Analysis of Shocks and the Cycle in a Model of Output and Employment
1999
There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. Our aim is to propose a statistical model that offers a congruent representation of post-war US employment and output data. We use a cointegrated vector autoregressive Markov-switching model where some parameters are changing according to phase of the business and employment cycle. Employment and output are found to have a common cyclical component and the long run dynamics are characterized by a cointegrating vector including employment and output and a trend as a proxy for technological progress and capital accumulation. Short-run and long-run dynamics are jointly estimated in a Markov-switching vector-equilibrium-correction model with three regimes representing recession, growth and high growth. For the analysis of the dynamics of output and employment, a new set of impulse-response exercises is proposed.
Modelling and Analyzing Turkish Business Cycles through Markov-Switching Models
Business and Economic Research
This study uses the different versions of the Markov-Switching methodology for modeling business cycles in Turkey and determining their turning points through quarterly real GDP figures for the 1987-2021 period. Based on the results obtained from the models, the recovery periods in Turkey last approximately 8.5 quarters and exhibit long and permanent nature while contraction periods are short, variable, and temporary, lasting around 4 quarters on average. The estimated Markov-Switching models mostly produce the same turning points. The compatibility of the obtained results with the national and international developments experienced during the analyzing period indicates the consistency of the developed models. On the other hand, the results reveal the importance of consistent and credible monetary and fiscal policies in smoothing business cycles.
Using Regional Cycles to Measure National Business Cycles in the U.S. with the Markov Switching Panel Model
Economics Bulletin, 2007
This paper measures the accuracy of using regional cycles to identify national business cycle turning points in the U.S. with the Markov Switching Panel (MSP) model. Based on the MSP model, it is determined that regional cycles are highly capable of identifying national business cycle turning points in the U.S., but the duration of recessions of regional cycles are longer than those of national business cycles.
Decomposing the Ins and Outs of Cyclical Unemployment
SSRN Electronic Journal, 2000
This paper analyzes the contribution of the socioeconomic and demographic composition of the pool of employed and unemployed individuals to the dynamics of the labor market in diff erent phases of the business cycle. Using individual level data from the Current Population Survey (CPS), we decompose diff erences in employment status transition rates between economic upswings and downturns into composition eff ects and behavioral eff ects. We fi nd that overall composition eff ects play a minor role for the cyclicality of the unemployment outfl ow rate, although the contribution of the duration of unemployment is signifi cant. In contrast, composition eff ects dampen the cyclicality of the unemployment infl ow rate considerably. We further observe that the initially positive contribution of composition eff ects to a higher unemployment outfl ow rate turns negative over the course of the recession. JEL Classifi cation: J63, J64, J21, E24
Business cycle asymmetries: Characterisation and testing based on Markov-switching autoregressions
1998
We propose testing for business cycle asymmetries in Markov-switching autoregressive (MS-AR) models. We derive the parametric restrictions on MS-AR models that rule out types of asymmetries such as deepness, steepness, and sharpness, and set out a testing procedure based on Wald statistics which have standard asymptotics. For a two-regime model, such as that popularised by Hamilton (1989), we show that deepness implies sharpness (and vice versa) while the process is always nonsteep. We illustrate with two and three-state MS models of US GNP growth, and with models of US output and employment. Our findings are compared with those obtained from standard nonparametric tests.
Related papers
A Markov-switching vector equilibrium correction model of the UK labour market
Empirical Economics, 2002
There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. Our aim is to propose a statistical model that offers a congruent representation of post-war UK labour market. We use a cointegrated vector autoregressive Markov-switching model where some parameters change according to the phase of the business cycle. Output, employment, labour supply and real earnings are found to have a common cyclical component. The long run dynamics are characterized by two cointegrating vectors: trend-adjusted labour productivity and the labour share. Despite there having been many changes affecting this sector of the UK economy, the Markov-switching vector-equilibrium-correction model with three regimes representing recession, growth and high growth provides a good characterization of the sample data over the period 1966(3)-1993(1) In an out-of-sample forecast experiment over the period 1991(2)-1993(1) it beats linear and non-linear model alternatives. The results of an impulse-response analysis highlight the dangers of using VARs when the constancy of the estimated coefficients has not been established.
Identification and Normalization in Markov Switching Models of 'Business Cycles
SSRN Electronic Journal, 2000
for helpful comments and Chang-Jin Kim for providing them with his data. Computations in this paper were carried out, in part, using the BACC software developed by John Geweke and Siddhartha Chib (http://www.econ.umn.edu/˜bacc/), and James LeSage's Applied Econometrics Toolbox for Matlab (www.spatial-econometrics.com). The authors retain all responsibility for any remaining errors. The views expressed herein are those of the authors and do not necessarily represent those of the Federal Reserve Bank of Kansas City or the Federal Reserve System.
A Disaggregated Markov-Switching Model of the Business Cycle In UK Manufacturing
The Manchester School, 2000
Exploring index of production data for six major UK manufacturing sectors, this paper investigates the interaction of the UK business cycle with changes in the industrial structure of the UK economy during the last three decades. We propose a Markov-switching vector equilibrium correction model with three regimes representing recession, normal growth and high growth. The regime shifts simultaneously affect the common growth rate and the sectoral equilibrium allocation of industrial production. In contrast to previous investigations, a common cycle can be uncovered which is closely related to traditional datings of the UK business cycle.
A New Approach to the Analysis of Business Cycle Transitions in a Model of Output and Employment
2001
This paper proposes a new framework for the impulse-response analysis of business cycle transitions. A cointegrated vector autoregressive Markov-switching model is found to be a congruent representation of post-war US employment and output data. In this model some parameters change according to the phase of the business cycle which effects employment and output simultaneously. The long run dynamics are characterized by a cointegrating vector including employment, output and a trend as a proxy for technological progress and capital accumulation. Short-run and long-run dynamics are jointly estimated in a Markov-switching vector-equilibrium-correction model with three regimes representing recession, growth and high growth. For the analysis of the dynamics of output and employment, a new set of impulse-response exercises is considered.
A Markov Switching Regime Model of the Brazilian Business Cycle
SSRN Electronic Journal, 2000
Previous studies have shown that linear models are incapable of capturing business cycle dynamics with accuracy. This has brought interest in non-linear models such as the Markov switching (MS) regime technique, which can distinguish business cycle recession and expansion phases, and is sufficiently flexible to allow different relationships to apply over these phases. This technique can be used to simultaneously estimate the data generating process of real GDP growth and classify each observation into one of two regimes (i.e. lowgrowth and high-growth regimes). In this study, we investigate the dynamics of the Brazilian business cycle using a Markov regime switching vector autoregressive model (MS-VAR). The study was developed using time-variable transition probabilities (TVTP) and for comparison and validation, fixed transition probabilities (FTP) between regimes. In order to capture cyclical fluctuations of the Brazilian GDP, we use the yield spread as a leading indicator. Most of the results obtained with the MS-VAR-TVTP are according to the expected. We show that the model is adequate to predict short-term cyclical fluctuations in the Brazilian economy. We also estimate an MS-VAR model with FTP in order to validate the TVTP model. We confirm the relevance of the yield spread in the estimation of the model parameters and the transition probabilities.
Dynamic employment adjustments over business cycles
Empirical Economics, 2005
This paper uses U.S. monthly industrial production employment data between 1964 and 2000 to examine the dynamic labor adjustments of production workers and nonproduction workers in both the short and long-run. The results from the short-run analysis show that the dynamic adjustment of production workers is consistent with business cycles. However, the adjustment of nonproduction workers is relatively fixed, lags behind the shocks over business cycle changes, and exhibits the quasi-fixed factor property. In the long-run, we found that nonproduction workers and production workers are cointegrated indicating that the two series are in long-run equilibrium. JEL Classification Codes: C320, J210, J500.
Unemployment rate and wage growth in Brazil: evidence from a Markov-switching model
2020
This paper has the purpose to investigate the relationship between unemployment rate and wage growth for the Brazilian economy from 2000to 2016, by means of a Markov-switching regression model. The empirical approach is based on the New-Keynesian Phillips Curve developed by Gali (2011). The estimation results suggest the existence of two well definedregimes, one characterized by the non-validation of the Phillips Curve, while in the other the trade-off between unemployment and wageinflation is validated, with the economic cycle being a key factor in regime switching.
Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies
2007
The appropriately selected leading indicators can substantially improve the forecasting of the peaks and troughs of the business cycle. Using the novel methodology of the dynamic bi-factor model with Markov switching and the data for three largest European economies (France, Germany, and UK) we construct composite leading indicator (CLI) and composite coincident indicator (CCI) as well as corresponding recession probabilities. We estimate also a rival model of the Markov-switching VAR in order to see, which of the two models brings better outcomes. The recession dates derived from these models are compared to three reference chronologies: those of OECD and ECRI (growth cycles) and those obtained with quarterly Bry-Boschan procedure (classical cycles). Dynamic bi-factor model and MSVAR appear to predict the cyclical turning points equally well without systematic superiority of one model over another
Finance and the Business Cycle: a Kalman Filter Approach with Markov Switching
Working Papers Series, 2005
This paper combines two popular econometric tools, the dynamic factor model and the Markov-Switching model, to consider three segments of the financial system-the stock market, debt, and money-and their contribution to US business cycles over the past four decades. The dynamic factor model identifies a composite factor index for each financial segment, and using Markov-switching models by Hamilton (1989) and Filardo (1994), this paper then estimates the effect of each segment index on business cycle behaviour. This ...
Markov-Switching Procedures for Dating the Euro-Zone Business Cycle
Vierteljahrshefte zur Wirtschaftsforschung, 2001
This paper addresses the issues of identification and dating of the Euro-zone business cycle by using the Markov-switching approach innovated by Hamilton in his analysis of the US business cycle. Regime shifts in the stochastic process of economic growth in the Euro-zone are identified by fitting Markov-switching models to aggregated and single-country Euro-zone real GDP growth data of the last two decades. The models are found to be statistically congruent and economically meaningful. Based of the smoothed regime probabilities from the Markov-switching models the Euro-zone business cycle is dated and recessions from 1980Q1 to 1981Q1 and 1992Q3 to 1993Q2 are revealed. A Markov-switching vector autoregression of real GDP growth rates in eight EMU member states shows that while the business cycles in the Euro-zone have not been perfectly synchronized over the last two decades, the overall evidence for the presence of a common Euro-zone cycle is strong.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.